Skip to main content
Springer Nature Link
Log in

Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV)

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11744))

Included in the following conference series:

Abstract

The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. The simulation and experimental results show the validity and effectiveness of the proposed algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Open source implementation of the presented algorithm as a ROS package. https://github.com/kucars/sspp

  2. Gazebo (2015). http://gazebosim.org/

  3. Alexis, K., Papachristos, C., Siegwart, R., Tzes, A.: Uniform coverage structural inspection path-planning for micro aerial vehicles. In: IEEE International Symposium on Intelligent Control - Proceedings, October 2015, pp. 59–64 (2015). https://doi.org/10.1109/ISIC.2015.7307280

  4. Almadhoun, R., Taha, T., Seneviratne, L., Dias, J., Cai, G.: Aircraft inspection using unmanned aerial vehicles. In: International Micro Air Vehicle Competition and Conference, pp. 43–49 (2016). http://www.imavs.org/papers/2016/43_IMAV2016_Proceedings.pdf

  5. Almadhoun, R., Taha, T., Seneviratne, L., Dias, J., Cai, G.: GPU accelerated coverage path planning optimized for accuracy in robotic inspection applications. In: 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 1–4 (2016). https://doi.org/10.1109/MWSCAS.2016.7869968

  6. Atkar, P.N., Conner, D.C., Greenfield, A., Choset, H.: Hierarchical segmentation of surfaces embedded in R3 for auto-body painting. Algorithmic Found. Robot. VI 1, 27–42 (2005)

    Article  Google Scholar 

  7. Bircher, A., et al.: Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics, pp. 6423–6430 (2015)

    Google Scholar 

  8. Bircher, A., et al.: Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots. Auton. Robots (2015). https://doi.org/10.1007/s10514-015-9517-1

    Article  Google Scholar 

  9. Cheng, P., Keller, J., Kumar, V.: Time-optimal UAV trajectory planning for 3D urban structure coverage. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 2750–2757 (2008). https://doi.org/10.1109/IROS.2008.4650988

  10. Christofides, N.: Worst-Case Analysis of a New Heuristic Prepared for the Travelling Salesman Problem, February 1976

    Google Scholar 

  11. Dornhege, C., Kleiner, A., Kolling, A.: Coverage search in 3D. In: 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2013 (2013). https://doi.org/10.1109/SSRR.2013.6719340

  12. Englot, B., Hover, F.: Inspection planning for sensor coverage of 3D marine structures. In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings, pp. 4412–4417 (2010). https://doi.org/10.1109/IROS.2010.5648908

  13. Englot, B., Hover, F.: Sampling-based coverage path planning for inspection of complex structures. In: ICAPS, pp. 29–37 (2012)

    Google Scholar 

  14. Englot, B., Hover, F.S.: Sampling-based sweep planning to exploit local planarity in the inspection of complex 3D structures. In: IEEE International Conference on Intelligent Robots and Systems, pp. 4456–4463 (2012). https://doi.org/10.1109/IROS.2012.6386126

  15. Furrer, F., Burri, M., Achtelik, M., Siegwart, R.: RotorS—a modular Gazebo MAV simulator framework. In: Koubaa, A. (ed.) Robot Operating System (ROS): The Complete Reference (Volume 1). SCI, vol. 625, pp. 595–625. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26054-9_23

    Chapter  Google Scholar 

  16. Galceran, E., Carreras, M.: A survey on coverage path planning for robotics. Robot. Auton. Syst. 61(12), 1258–1276 (2013). https://doi.org/10.1016/j.robot.2013.09.004

    Article  Google Scholar 

  17. Ground, A., Uav, V.: A hybrid path planning method in unmanned. IEEE Trans. Veh. Technol. 65(12), 9585–9596 (2016). https://doi.org/10.1109/TVT.2016.2623666

    Article  Google Scholar 

  18. Haner, S., Heyden, A.: Discrete Optimal View Path Planning (2011)

    Google Scholar 

  19. Helsgaun, K.: Effective implementation of the Lin-Kernighan traveling salesman heuristic. Eur. J. Oper. Res. 126(1), 106–130 (2000). https://doi.org/10.1016/S0377-2217(99)00284-2

    Article  MathSciNet  MATH  Google Scholar 

  20. Heng, L., Gotovos, A., Krause, A., Pollefeys, M.: Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments. In: IEEE International Conference on Robotics and Automation (2015)

    Google Scholar 

  21. Hong, S.: Accelerating CUDA graph algorithms at maximum warp. ACM SIGPLAN Not. 46, 267–276 (2011)

    Article  Google Scholar 

  22. Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robots 34(3), 189–206 (2013). https://doi.org/10.1007/s10514-012-9321-0

    Article  Google Scholar 

  23. Hover, F.S., et al.: Advanced perception, navigation and planning for autonomous in-water ship hull inspection. Int. J. Robot. Res. 31(12), 1445–1464 (2012). https://doi.org/10.1177/0278364912461059

    Article  Google Scholar 

  24. Janousek, P., Faigl, J.: Speeding up coverage queries in 3D multi-goal path planning. In: Proceedings - IEEE International Conference on Robotics and Automation, vol. 1, pp. 5082–5087 (2013). https://doi.org/10.1109/ICRA.2013.6631303

  25. Karaman, S., Frazzoli, E.: Sampling-based algorithms for optimal motion planning. Int. J. Robot. Res. 30(7), 846–894 (2011). https://doi.org/10.1177/0278364911406761

    Article  MATH  Google Scholar 

  26. Khoshelham, K., Elberink, S.O.: Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors 12(12), 1437–1454 (2012). https://doi.org/10.3390/s120201437

    Article  Google Scholar 

  27. Krainin, M., Curless, B., Fox, D.: Autonomous generation of complete 3D object models using next best view manipulation planning. In: Proceedings - IEEE International Conference on Robotics and Automation, pp. 5031–5037 (2011). https://doi.org/10.1109/ICRA.2011.5980429

  28. Labbe, M., Michaud, F.: Online global loop closure detection for large-scale multi-session graph-based SLAM. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2661–2666 (2014)

    Google Scholar 

  29. Luo, C., Mcclean, S.I., Parr, G., Teacy, L., Nardi, R.D.: UAV position estimation and collision avoidance using the extended Kalman filter. IEEE Trans. Veh. Technol. 62(6), 2749–2762 (2013). https://doi.org/10.1109/TVT.2013.2243480

    Article  Google Scholar 

  30. Optitrack, 25 March 2017. http://www.optitrack.com/

  31. Papadopoulos, G., Kurniawati, H., Patrikalakis, N.M.: Asymptotically optimal inspection planning using systems with differential constraints, pp. 4111–4118 (2013)

    Google Scholar 

  32. PX4, 16 July 2015. http://px4.io/

  33. Qin, H., et al.: Autonomous exploration and mapping system using heterogeneous UAVs and UGVs in GPS-denied environments. IEEE Trans. Veh. Technol. PP(c), 1 (2018). https://doi.org/10.1109/TVT.2018.2890416

    Article  Google Scholar 

  34. ROS, 16 July 2015. http://www.ros.org/

  35. Scott, W.R.: Model-based view planning. Mach. Vis. Appl. 20(1), 47–69 (2009). https://doi.org/10.1007/s00138-007-0110-2

    Article  MathSciNet  MATH  Google Scholar 

  36. Scott, W.R., Roth, G., Rivest, J.F.: View planning for automated three-dimensional object reconstruction and inspection. ACM Comput. Surv. 35(1), 64–96 (2003). https://doi.org/10.1145/641865.641868

    Article  Google Scholar 

  37. Sehestedt, S., Paul, G., Rushton-smith, D., Liu, D.: Prior-knowledge assisted fast 3D map building of structured environments for steel bridge maintenance, pp. 1040–1046 (2013)

    Google Scholar 

  38. Trummer, M., Munkelt, C., Denzler, J.: Online next-best-view planning for accuracy optimization using an extended E-criterion. In: Proceedings - International Conference on Pattern Recognition, pp. 1642–1645 (2010). https://doi.org/10.1109/ICPR.2010.406

  39. Valente, J., Barrientos, A., Cerro, J.D.: Coverage path planning to survey large outdoor areas with aerial robots: a comprehensive analysis. In: Introduction to Modern Robotics (2011)

    Google Scholar 

  40. Wallar, A., Plaku, E., Sofge, D.A.: A planner for autonomous risk-sensitive coverage (PARC OV ) by a team of unmanned aerial vehicles. In: IEEE Symposium on Swarm Intelligence (SIS) (2014). https://doi.org/10.1109/SIS.2014.7011807

Download references

Acknowledgements

This publication is based upon work supported by the Khalifa University of Science and Technology under Award No. RC1-2018-KUCARS.

Author information

Authors and Affiliations

  1. Khalifa University of Science and Technology, Abu Dhabi, UAE

    Randa Almadhoun, Jorge Dias, Lakmal Seneviratne & Yahya Zweiri

  2. Algorythma’s Autonomous Aerial Lab, Abu Dhabi, UAE

    Tarek Taha

  3. Faculty of Science, Engineering and Computing, Kingston University London, London, SW15 3DW, UK

    Yahya Zweiri

Authors
  1. Randa Almadhoun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tarek Taha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jorge Dias
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lakmal Seneviratne
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yahya Zweiri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Randa Almadhoun .

Editor information

Editors and Affiliations

  1. Shenyang Institute of Automation, Shenyang, China

    Haibin Yu

  2. Shenyang Institute of Automation, Shenyang, China

    Jinguo Liu

  3. Shenyang Institute of Automation, Shenyang, China

    Lianqing Liu

  4. University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  5. Shenyang Institute of Automation, Shenyang, China

    Yuwang Liu

  6. University of Portsmouth, Portsmouth, UK

    Dalin Zhou

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Almadhoun, R., Taha, T., Dias, J., Seneviratne, L., Zweiri, Y. (2019). Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV). In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11744. Springer, Cham. https://doi.org/10.1007/978-3-030-27541-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27541-9_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27540-2

  • Online ISBN: 978-3-030-27541-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics